Richard Socher

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Richard ∙ Salesforce

Chief Scientist at Salesforce, Adjunct Professor at Stanford

Evaluating State-of-the-Art Classification Models Against Bayes Optimality

Evaluating the inherent difficulty of a given data-driven classification...
06/07/2021 ∙ by Ryan Theisen, et al. ∙ 0 ∙ share

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Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization

The early phase of training has been shown to be important in two ways f...
12/28/2020 ∙ by Stanisław Jastrzębski, et al. ∙ 16 ∙ share

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Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing

We present BRIDGE, a powerful sequential architecture for modeling depen...
12/23/2020 ∙ by Xi Victoria Lin, et al. ∙ 0 ∙ share

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Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference

Intent detection is one of the core components of goal-oriented dialog s...
10/25/2020 ∙ by Jian-Guo Zhang, et al. ∙ 10 ∙ share

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Online Structured Meta-learning

Learning quickly is of great importance for machine intelligence deploye...
10/22/2020 ∙ by Huaxiu Yao, et al. ∙ 6 ∙ share

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Explaining and Improving Model Behavior with k Nearest Neighbor Representations

Interpretability techniques in NLP have mainly focused on understanding ...
10/18/2020 ∙ by Nazneen Fatema Rajani, et al. ∙ 0 ∙ share

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Explaining Creative Artifacts

Human creativity is often described as the mental process of combining a...
10/14/2020 ∙ by Lav R. Varshney, et al. ∙ 0 ∙ share

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Universal Natural Language Processing with Limited Annotations: Try Few-shot Textual Entailment as a Start

A standard way to address different NLP problems is by first constructin...
10/06/2020 ∙ by Wenpeng Yin, et al. ∙ 0 ∙ share

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GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing

We present GraPPa, an effective pre-training approach for table semantic...
09/29/2020 ∙ by Tao Yu, et al. ∙ 1 ∙ share

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Composed Variational Natural Language Generation for Few-shot Intents

In this paper, we focus on generating training examples for few-shot int...
09/21/2020 ∙ by Congying Xia, et al. ∙ 0 ∙ share

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GeDi: Generative Discriminator Guided Sequence Generation

Class-conditional language models (CC-LMs) can be used to generate natur...
09/14/2020 ∙ by Ben Krause, et al. ∙ 0 ∙ share

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Central Yup'ik and Machine Translation of Low-Resource Polysynthetic Languages

Machine translation tools do not yet exist for the Yup'ik language, a po...
09/09/2020 ∙ by Christopher Liu, et al. ∙ 0 ∙ share

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Photon: A Robust Cross-Domain Text-to-SQL System

Natural language interfaces to databases (NLIDB) democratize end user ac...
07/30/2020 ∙ by Jichuan Zeng, et al. ∙ 13 ∙ share

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SummEval: Re-evaluating Summarization Evaluation

The scarcity of comprehensive up-to-date studies on evaluation metrics f...
07/24/2020 ∙ by Alexander R. Fabbri, et al. ∙ 0 ∙ share

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DART: Open-Domain Structured Data Record to Text Generation

We introduce DART, a large dataset for open-domain structured data recor...
07/06/2020 ∙ by Dragomir Radev, et al. ∙ 0 ∙ share

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Theory-Inspired Path-Regularized Differential Network Architecture Search

Despite its high search efficiency, differential architecture search (DA...
06/30/2020 ∙ by Pan Zhou, et al. ∙ 0 ∙ share

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BERTology Meets Biology: Interpreting Attention in Protein Language Models

Transformer architectures have proven to learn useful representations fo...
06/26/2020 ∙ by Jesse Vig, et al. ∙ 0 ∙ share

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Towards Understanding Hierarchical Learning: Benefits of Neural Representations

Deep neural networks can empirically perform efficient hierarchical lear...
06/24/2020 ∙ by Minshuo Chen, et al. ∙ 5 ∙ share

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A High-Quality Multilingual Dataset for Structured Documentation Translation

This paper presents a high-quality multilingual dataset for the document...
06/24/2020 ∙ by Kazuma Hashimoto, et al. ∙ 0 ∙ share

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CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization

The COVID-19 global pandemic has resulted in international efforts to un...
06/17/2020 ∙ by Andre Esteva, et al. ∙ 11 ∙ share

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WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos

Online action detection in untrimmed videos aims to identify an action a...
06/05/2020 ∙ by Mingfei Gao, et al. ∙ 0 ∙ share

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EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

The goal of conversational machine reading is to answer user questions g...
05/26/2020 ∙ by Yifan Gao, et al. ∙ 0 ∙ share

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Prototypical Contrastive Learning of Unsupervised Representations

This paper presents Prototypical Contrastive Learning (PCL), an unsuperv...
05/11/2020 ∙ by Junnan Li, et al. ∙ 10 ∙ share

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It's Morphin' Time! Combating Linguistic Discrimination with Inflectional Perturbations

Training on only perfect Standard English corpora predisposes pre-traine...
05/09/2020 ∙ by Samson Tan, et al. ∙ 0 ∙ share

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A Simple Language Model for Task-Oriented Dialogue

Task-oriented dialogue is often decomposed into three tasks: understandi...
05/02/2020 ∙ by Ehsan Hosseini-Asl, et al. ∙ 0 ∙ share

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ESPRIT: Explaining Solutions to Physical Reasoning Tasks

Neural networks lack the ability to reason about qualitative physics and...
05/02/2020 ∙ by Nazneen Fatema Rajani, et al. ∙ 0 ∙ share

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The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies

Tackling real-world socio-economic challenges requires designing and tes...
04/28/2020 ∙ by Stephan Zheng, et al. ∙ 7 ∙ share

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ToD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogues

The use of pre-trained language models has emerged as a promising direct...
04/15/2020 ∙ by Chien-Sheng Wu, et al. ∙ 0 ∙ share

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Improving out-of-distribution generalization via multi-task self-supervised pretraining

Self-supervised feature representations have been shown to be useful for...
03/30/2020 ∙ by Isabela Albuquerque, et al. ∙ 0 ∙ share

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Towards Noise-resistant Object Detection with Noisy Annotations

Training deep object detectors requires significant amount of human-anno...
03/03/2020 ∙ by Junnan Li, et al. ∙ 2 ∙ share

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Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning

We introduce a parameterization method called Neural Bayes which allows ...
02/20/2020 ∙ by Devansh Arpit, et al. ∙ 36 ∙ share

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Tree-structured Attention with Hierarchical Accumulation

Incorporating hierarchical structures like constituency trees has been s...
02/19/2020 ∙ by Xuan-Phi Nguyen, et al. ∙ 0 ∙ share

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Non-Autoregressive Dialog State Tracking

Recent efforts in Dialogue State Tracking (DST) for task-oriented dialog...
02/19/2020 ∙ by Hung Le, et al. ∙ 7 ∙ share

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DivideMix: Learning with Noisy Labels as Semi-supervised Learning

Deep neural networks are known to be annotation-hungry. Numerous efforts...
02/18/2020 ∙ by Junnan Li, et al. ∙ 0 ∙ share

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Taylorized Training: Towards Better Approximation of Neural Network Training at Finite Width

We propose Taylorized training as an initiative towards better understan...
02/10/2020 ∙ by Yu Bai, et al. ∙ 20 ∙ share

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Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills

Acquiring abilities in the absence of a task-oriented reward function is...
02/10/2020 ∙ by Victor Campos, et al. ∙ 11 ∙ share

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Limits of Detecting Text Generated by Large-Scale Language Models

Some consider large-scale language models that can generate long and coh...
02/09/2020 ∙ by Lav R. Varshney, et al. ∙ 0 ∙ share

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Learning from Noisy Anchors for One-stage Object Detection

State-of-the-art object detectors rely on regressing and classifying an ...
12/11/2019 ∙ by Hengduo Li, et al. ∙ 12 ∙ share

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Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering

Answering questions that require multi-hop reasoning at web-scale necess...
11/24/2019 ∙ by Akari Asai, et al. ∙ 0 ∙ share

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Attentive Student Meets Multi-Task Teacher: Improved Knowledge Distillation for Pretrained Models

In this paper, we explore the knowledge distillation approach under the ...
11/09/2019 ∙ by Linqing Liu, et al. ∙ 0 ∙ share

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ERASER: A Benchmark to Evaluate Rationalized NLP Models

State-of-the-art models in NLP are now predominantly based on deep neura...
11/08/2019 ∙ by Jay DeYoung, et al. ∙ 35 ∙ share

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Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards

While using shaped rewards can be beneficial when solving sparse reward ...
11/04/2019 ∙ by Alexander Trott, et al. ∙ 8 ∙ share

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Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework

Human-like chit-chat conversation requires agents to generate responses ...
10/28/2019 ∙ by Michael Shum, et al. ∙ 0 ∙ share

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Evaluating the Factual Consistency of Abstractive Text Summarization

Currently used metrics for assessing summarization algorithms do not acc...
10/28/2019 ∙ by Wojciech Kryściński, et al. ∙ 0 ∙ share

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Global Capacity Measures for Deep ReLU Networks via Path Sampling

Classical results on the statistical complexity of linear models have co...
10/22/2019 ∙ by Ryan Theisen, et al. ∙ 23 ∙ share

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Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking

Dialog State Tracking (DST) is a core component in task-oriented dialog ...
10/08/2019 ∙ by Jian-Guo Zhang, et al. ∙ 23 ∙ share

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Entropy Penalty: Towards Generalization Beyond the IID Assumption

It has been shown that instead of learning actual object features, deep ...
10/01/2019 ∙ by Devansh Arpit, et al. ∙ 11 ∙ share

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CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases

We present CoSQL, a corpus for building cross-domain, general-purpose da...
09/11/2019 ∙ by Tao Yu, et al. ∙ 39 ∙ share

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CTRL: A Conditional Transformer Language Model for Controllable Generation

Large-scale language models show promising text generation capabilities,...
09/11/2019 ∙ by Nitish Shirish Keskar, et al. ∙ 0 ∙ share

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Pretrained AI Models: Performativity, Mobility, and Change

The paradigm of pretrained deep learning models has recently emerged in ...
09/07/2019 ∙ by Lav R. Varshney, et al. ∙ 0 ∙ share

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Richard Socher

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